We are rapidly moving into a world where one person can easily use six different modes of transportation in a single day. Mobility behavior is becoming more complex. As a result, transportation planners need to be able to analyze past behavior, measure current changes, and forecast future demand for more modes of travel than their predecessors.
Every type of travel counts, from bike shares to the “gig economy” created by transportation network providers and delivery apps. Unfortunately, not every mode is being counted. It’s simply not possible with conventional transportation data collection methods.
That’s why StreetLight Data launched our new Multimodal Measurement Initiative. Our goal is to launch a new suite of Metrics. These Metrics will measure brand-new modes, older modes of transport that have always been difficult to measure, and how all of these modes interact. Do you want to participate?
Our goal is to launch a new suite of Metrics in 2018 that cover old modes that have always been difficult to measure as well as the brand-new modes that are changing the way people travel today.
Join Our Working Group
Our Multimodal Measurement (M2) Initiative will build on several successfully completed pilot projects focused on bike, pedestrian, and gig economy analytics. However, before we make these analytics broadly available to clients across the US and Canada, we would like to conduct additional validation studies.
We’re looking for partners who need multimodal transportation analytics and that have projects for this summer and early fall. We hope to find partners who have some previously collected data about our target modes, or who plan on collecting some using non-Big Data methods during the project. The working group will include:
- Government agencies
- Academic institutions
- Private transportation firms
- Multimodal data providers
Do you want to join? The first step to join is to sign up here. A limited number of partners will be selected to participate. While not required, priority will be given to organizations that can share well-validated multimodal travel data.
Types of data we’re looking for include: surveys, multimodal data from other types of sensors, mode-specific app data, GPS travel diaries, and more.
Once additional projects are completed successfully, we will add new multimodal Metrics to StreetLight InSight®. (StreetLight InSight is our on-demand platform for transforming geospatial Big Data from mobile devices into actionable analytics for transportation.)
Why Multimodal Measurement Matters
In some cities, autonomous vehicles are already sharing the road with pedestrians, cyclists, electric scooters, buses, commercial trucks, and personal vehicles. Flying cars are closer to reality than you might expect. However, many communities are not ready for these new modes. In San Francisco, where StreetLight Data is headquartered, electric scooters were recently thrown into the bay – most likely as one resident’s form of protest.
Without the right tools to measure and model each of these modes and their interactions, we cannot plan the infrastructure and policies required to manage them. The time is right to tackle the challenge of multimodal measurement and modal interaction. Consider these statistics from Beyond Traffic 2045, a report published by the US Department of Transportation in January 2017:
- Nearly 1 in 5 young adults in the US do not have a driver’s license.
- In 2009, Americans aged 18 to 34 drove 21% fewer miles than Americans in that age group drove in 2001.
- The number of Americans over age 65 who use public transit increased by about 40% from 2006 to 2016.
- By 2045, the number of Americans over age 65 is expected to double. About one-third of Americans in that age group have a disability that restricts their mobility.
It’s clear from these trends that the measuring vehicle trips alone is not enough. To plan a transportation future that is sustainable, equitable, and efficient, we must have empirical, comprehensive multimodal measurement.
With high-quality validation data and the right partners, StreetLight Data will make empirical, comprehensive multimodal measurement a reality.
